一项原则被强调，即即使是机器学习产生的算法错误，人类也仍然需要负责。这一概念强调，当系统出错或产生负面结果时，“算法做的”这种借口是不够的。讨论引用了“基金会可问责算法”和BBC新闻文章的资源。 AI
影响 强化了AI开发和部署的伦理框架，强调了人类监督。
排序理由 该集群讨论了关于AI问责制的原则，引用了外部来源，而不是宣布新的发展。
在 Mastodon — fosstodon.org 阅读 →
AI 生成摘要 · Google Gemini · 来自 3 个来源。 我们如何撰写摘要 →
社交平台强调AI错误的人类问责制
报道来源 [3]
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总有人要负责 原则“算法干的”在算法系统出错或产生不良后果时不是一个可接受的借口
There is always a human responsible Principle '"The algorithm did it" is not an acceptable excuse if algorithmic systems make mistakes or have undesired consequences, including from machine-learning processes' Claims www.bbc.com/news/article... www.bbc.com/news/article... #AI @ab…
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总有人要负责 原则：“算法干的”不是系统出错或产生不良后果的可接受借口
There is always a human responsible Principle '"The algorithm did it" is not an acceptable excuse if algorithmic systems make mistakes or have undesired consequences, including from machine-learning processes' Claims https://www. bbc.com/news/articles/cz7dl7w8 y7po https://www. b…
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总有人要负责 原则“算法做的”不是借口 算法系统出错或产生不良后果时
There is always a human responsible Principle '"The algorithm did it" is not an acceptable excuse if algorithmic systems make mistakes or have undesired consequences, including from machine-learning processes' Claims www.bbc.com/news/article... www.bbc.com/news/article... #AI @ab…